ASR Comparison: Base whisper-large-v3 vs. whisper-large-v3-NSC vs. MERaLiON-AudioLLM-Whisper-SEA-LION
Reference

they help they got the elders' club

Base Model Prediction

Yeah, they help, they got the elders club.

Fine-Tuned Model Prediction

ya they help they got the elders' club

MERaLiON Model Prediction

<Speaker1>: Ya, they help they got the elders club.

Reference

they do they do

Base Model Prediction

They do. Yeah, they need to keep the

Fine-Tuned Model Prediction

they do they do

MERaLiON Model Prediction

<Speaker1>: They do ya, they need to keep like the.

Reference

so they usually they usually have more armor

Base Model Prediction

So they usually have more armor

Fine-Tuned Model Prediction

so they usually they usually have more armor

MERaLiON Model Prediction

<Speaker1>: So they usually, they usually have more armour.

Reference

crab more should be okay what don't

Base Model Prediction

I think crab moss should be okay.

Fine-Tuned Model Prediction

crab more should be okay what

MERaLiON Model Prediction

<Speaker1>: Crab more should be okay [lah] <Speaker2>: Should be.

Reference

oh is it when I watch with you that last time

Base Model Prediction

Oh, you see when I watched you do that last time?

Fine-Tuned Model Prediction

oh is it when I watch with you that last time

MERaLiON Model Prediction

<Speaker1>: [oh] you see when I watch few that last time ya?

Reference

so now I'm suppose to talk about my

Base Model Prediction

So now I'm supposed to talk about my

Fine-Tuned Model Prediction

so now I'm supposed to talk about my

MERaLiON Model Prediction

<Speaker1>: So now Im supposed to talk about my?

Reference

a thousand plus lah more than thousand

Base Model Prediction

1000 plus, more than 1000.

Fine-Tuned Model Prediction

oh thousand plus lah more than thousand

MERaLiON Model Prediction

<Speaker1>: or thousand plus [ah] more than thousand

Reference

uh then then let me tell you this your goal

Base Model Prediction

Then let me tell you this, your girl

Fine-Tuned Model Prediction

uh let then let me tell you this your goal

MERaLiON Model Prediction

<Speaker1>: ** then let me tell you this is your goal

Reference

but aside from that like

Base Model Prediction

But aside from that,

Fine-Tuned Model Prediction

but aside from that like

MERaLiON Model Prediction

<Speaker1>: but aside from that like

Reference

that'll be probably be another what about what thirty forty years assuming they live a long life lah

Base Model Prediction

that will probably be another 30-40 years assuming they live a long life

Fine-Tuned Model Prediction

that will probably be another what what what thirty forty years assuming they live a long life lah

MERaLiON Model Prediction

<Speaker1>: that will probably be another what thirty forty years assuming they live A long life [lah]

Reference

ya

Base Model Prediction

Yeah.

Fine-Tuned Model Prediction

ya

MERaLiON Model Prediction

<Speaker1>: But we need.

Reference

ya

Base Model Prediction

Yeah.

Fine-Tuned Model Prediction

ya

MERaLiON Model Prediction

<Speaker1>: one

Reference

so next year not going with mum

Base Model Prediction

So next year, not great, Ma'am.

Fine-Tuned Model Prediction

so next year I'm not going with mum

MERaLiON Model Prediction

<Speaker1>: So next year I'm going with mum.

Reference

the teacher who make the biggest difference in your life is

Base Model Prediction

The teacher who make the biggest difference in your life is

Fine-Tuned Model Prediction

the teacher who make the biggest difference in your life is

MERaLiON Model Prediction

<Speaker1>: the teacher who made the biggest difference in your life is

Reference

feeding the shark oh no they are trying to

Base Model Prediction

feeding the no their channel

Fine-Tuned Model Prediction

feeding the shark oh no they are trying to

MERaLiON Model Prediction

<Speaker1>: Feeding the shark, No they are channel.

Reference

red

Base Model Prediction

Rick.

Fine-Tuned Model Prediction

red

MERaLiON Model Prediction

<Speaker1>: Rick

Reference

oh I never I think I knew it was chendol I just don't know what chendol is about to taste like but I like the twist one because it's uh

Base Model Prediction

I think I knew it was Chandor, I just don't know what Chandor is about to taste like, but I like the twist one because it's...

Fine-Tuned Model Prediction

oh I never I think I knew it was chendol I just don't know what chendol is supposed to taste like but I like the twist one because it's uh

MERaLiON Model Prediction

<Speaker1>: [oh] I never, I think I knew it was Chendol. I just don't know what Chendol is supposed to taste like, but I like the twist one because it's a. <Speaker2>: Correct.

Reference

my dad manage to

Base Model Prediction

my dad managed to

Fine-Tuned Model Prediction

my dad manage to

MERaLiON Model Prediction

<Speaker1>: my dad managed to

Reference

childhood and my parents err don't either don't have the resources or time to bring me out and err assuming I'm living right now and my parents are

Base Model Prediction

childhood and my parents either don't have the resources or time to bring me out and assuming I'm living right now and my parents are

Fine-Tuned Model Prediction

childhood and my parents err don't either don't have the resources or time to bring me out and err assuming I'm living right now and my parents are

MERaLiON Model Prediction

<Speaker1>: Childhood and my parents (uh) don't either, don't have the resources or time to bring me out, and (uh) assuming I'm leaving right now and my parents are.

Reference

what they can look forward in the school year

Base Model Prediction

what they can look forward in the school year

Fine-Tuned Model Prediction

what they can look forward in the school year

MERaLiON Model Prediction

<Speaker1>: what they can look forward in the school year

Reference

ee like Ant man

Base Model Prediction

E like Ant-Man

Fine-Tuned Model Prediction

ee like Ant man

MERaLiON Model Prediction

<Speaker1>: E like N man

Reference

name a favorite place

Base Model Prediction

Name a favorite place.

Fine-Tuned Model Prediction

name a favourite place

MERaLiON Model Prediction

<Speaker1>: name a favourite place

Reference

err what colour is he wearing

Base Model Prediction

What colour is he wearing?

Fine-Tuned Model Prediction

err what colour is he wearing

MERaLiON Model Prediction

<Speaker1>: (uh) what colour is he wearing?

Reference

alright sure

Base Model Prediction

I'll make sure.

Fine-Tuned Model Prediction

alright sure

MERaLiON Model Prediction

<Speaker1>: Or Rachel?

Reference

and I swear and he don't doesn't even know how to operate the washing machine and wash his own clothes

Base Model Prediction

And he doesn't even know how to operate the washing machine and wash his own clothes.

Fine-Tuned Model Prediction

and I swear and he don't doesn't even know how to operate the washing machine and wash his own clothes

MERaLiON Model Prediction

<Speaker1>: and I swear he doesn't even know how to operate a washing machine and wash his own clothes

Reference

ya the headlights and backlights

Base Model Prediction

Yellow headlights and backlights.

Fine-Tuned Model Prediction

ya the headlights and backlights

MERaLiON Model Prediction

<Speaker1>: yellow headlights and backlights

Reference

so it's like

Base Model Prediction

So it's like,

Fine-Tuned Model Prediction

so it's like

MERaLiON Model Prediction

<Speaker1>: Suicide.

Reference

ya and then you share with me ah mm I've never been to poly

Base Model Prediction

Yeah, and then he shared with me. I'd never been to Bali.

Fine-Tuned Model Prediction

ya then you share with me ah mm I never been to poly

MERaLiON Model Prediction

<Speaker1>: ya and then share with me [ah] I've never been to Poland

Reference

then it become like

Base Model Prediction

then it becomes like

Fine-Tuned Model Prediction

then it become like

MERaLiON Model Prediction

<Speaker1>: Then it become like.

Reference

beginners luck

Base Model Prediction

Begin as luck.

Fine-Tuned Model Prediction

beginners luck

MERaLiON Model Prediction

<Speaker1>: Beginners luck.

Reference

to talk about medical things in there it'll be useful translator thing

Base Model Prediction

We'll talk about medical things in there. It'll be a useful translator thing.

Fine-Tuned Model Prediction

we talk about medical things in there it will be a useful translator thing

MERaLiON Model Prediction

<Speaker1>: We talk about medical things in there, be a useful translator thing. <Speaker2>: Okay.

Reference

K lah maybe I have a lot of classroom moments okay and it's nothing from Poly

Base Model Prediction

maybe I have a lot of classroom moments okay and it's nothing from poly

Fine-Tuned Model Prediction

okay lah maybe I have a lot of classroom moments okay and starting from Poly

MERaLiON Model Prediction

<Speaker1>: Okay, [lah] maybe I have a lot of classroom moments okay and nothing from Poly.

Reference

what are your career goals and aspira~ aspiration aspiration means what ah

Base Model Prediction

What are your career goals and aspiration?

Fine-Tuned Model Prediction

what are your career goals and aspirae inspiration inspiration means what ah

MERaLiON Model Prediction

<Speaker1>: what are your career goals and aspire aspiration aspiration means what

Reference

ya that's eleven

Base Model Prediction

Yeah, that's 11.

Fine-Tuned Model Prediction

ya that's eleven

MERaLiON Model Prediction

<Speaker1>: nine IS eleven

Reference

they paint this white so the whole house is like

Base Model Prediction

they paint this white so the whole house is like

Fine-Tuned Model Prediction

they paint this white so the whole house is like

MERaLiON Model Prediction

<Speaker1>: They painted this white, so the whole house is like.

Reference

only two dollars only

Base Model Prediction

Only two doors, see?

Fine-Tuned Model Prediction

only two dollars okay

MERaLiON Model Prediction

<Speaker1>: only two dollars see.

Reference

I mean the pasar malam is like crazy ah I mean like everything got pasar malam that kind of thing

Base Model Prediction

I mean the Pasang Malam is like crazy. I mean like everything about Pasang Malam is like nothing.

Fine-Tuned Model Prediction

I mean the pasar malam is like crazy ah I mean like everything got pasar malam that kind of thing

MERaLiON Model Prediction

<Speaker1>: I mean the Pasar Malam is like crazy I mean everything got Pasar Malam you know thing

Reference

no K that day I went airport to study then

Base Model Prediction

No, okay, the day I went to the airport to study, then

Fine-Tuned Model Prediction

no okay that day I went airport to study then

MERaLiON Model Prediction

<Speaker1>: No, okay that day I went airport to study then.

Reference

rejected

Base Model Prediction

Rejected.

Fine-Tuned Model Prediction

rejected

MERaLiON Model Prediction

<Speaker1>: A and rejected it.

Reference

err I guess to me

Base Model Prediction

I guess we

Fine-Tuned Model Prediction

err I guess to me

MERaLiON Model Prediction

<Speaker1>: (uh) I guess to me.

Reference

then ya but when he gets older I think is a not

Base Model Prediction

But when he gets older, I think it's not

Fine-Tuned Model Prediction

then ya but when he gets older I think it's the not

MERaLiON Model Prediction

<Speaker1>: Then ya, but when he gets older, I think it's the not.

Reference

cause that will be weird you know it will be the super weird um

Base Model Prediction

because they'll be weird, you know? They'll be super weird.

Fine-Tuned Model Prediction

cause that will be weird you know it will be super weird um

MERaLiON Model Prediction

<Speaker1>: Cause thatll be weird, you know itll be super weird. (um)

Reference

he's wearing a green hat

Base Model Prediction

And he's wearing a green hat.

Fine-Tuned Model Prediction

he's wearing a green hat

MERaLiON Model Prediction

<Speaker1>: he is wearing A green hat

Reference

what distresses me

Base Model Prediction

what distresses me

Fine-Tuned Model Prediction

what destresses me

MERaLiON Model Prediction

<Speaker1>: What distresses me?

Reference

oh oh okay I I remember where is it because I always go and

Base Model Prediction

I remember where is it because I always go in.

Fine-Tuned Model Prediction

oh oh okay I I remember where is it because I always go and

MERaLiON Model Prediction

<Speaker1>: [oh] okay, I remember where is it because I always go and eat.

Reference

so is that counted as two differences

Base Model Prediction

So is that counted as two defenses?

Fine-Tuned Model Prediction

so is that counted as two differences

MERaLiON Model Prediction

<Speaker1>: So is that counted as two differences?

Reference

the uh

Base Model Prediction

The other...

Fine-Tuned Model Prediction

uh and

MERaLiON Model Prediction

<Speaker1>: So I told you already?

Reference

I guess now it helps me to

Base Model Prediction

I guess now it helps me to

Fine-Tuned Model Prediction

I guess now it helps me to

MERaLiON Model Prediction

<Speaker1>: I guess now it helps me to

Reference

it was like oh uh

Base Model Prediction

It was like, oh, uh,

Fine-Tuned Model Prediction

it was like oh uh

MERaLiON Model Prediction

<Speaker1>: It was like [oh] us.

Reference

okay Western food in general is very fried

Base Model Prediction

Okay, Western food in general is very flat.

Fine-Tuned Model Prediction

okay Western food in general is very fried

MERaLiON Model Prediction

<Speaker1>: okay, Western food in general is very flat

Reference

I open already

Base Model Prediction

I opened already.

Fine-Tuned Model Prediction

I open already

MERaLiON Model Prediction

<Speaker1>: I open already

Reference

like yeah you you get what I mean

Base Model Prediction

Oh, okay. You're trying out very

Fine-Tuned Model Prediction

like yeah you get what I mean

MERaLiON Model Prediction

<Speaker1>: [oh] okay, ya, you tried very best.

Reference

posting

Base Model Prediction

Most people...

Fine-Tuned Model Prediction

posting

MERaLiON Model Prediction

<Speaker1>: Most definitely.

Reference

mm ya but now they are ya but both of them not around so

Base Model Prediction

Yeah, but now they're not around.

Fine-Tuned Model Prediction

mm ya but now they are ya but both of them not around so

MERaLiON Model Prediction

<Speaker1>: Ya, but now they are ya, but both of them not around so.

Reference

marriage

Base Model Prediction

Yes. Marriage?

Fine-Tuned Model Prediction

marriage

MERaLiON Model Prediction

<Speaker1>: Yes, marriage.

Reference

plus

Base Model Prediction

glass

Fine-Tuned Model Prediction

plus

MERaLiON Model Prediction

<Speaker1>: Glass.

Reference

and go to jail

Base Model Prediction

and go to jail.

Fine-Tuned Model Prediction

and go to jail

MERaLiON Model Prediction

<Speaker1>: and go to jail

Reference

there will be come a time where they will reach a

Base Model Prediction

there will come a time when you reach a

Fine-Tuned Model Prediction

there will be come a time where they will reach a

MERaLiON Model Prediction

<Speaker1>: There will become a time where you reach A.

Reference

buy new clothes every few months they shop for new clothes new dresses

Base Model Prediction

buy new clothes every few months they shop for new clothes new dresses

Fine-Tuned Model Prediction

buy new clothes every few months they shop for new clothes new dresses

MERaLiON Model Prediction

<Speaker1>: buy new clothes every few months they shop for new clothes new dresses

Reference

do you get it because I don't get it

Base Model Prediction

Do you get it? Because I don't get it.

Fine-Tuned Model Prediction

do you get it because I don't get it

MERaLiON Model Prediction

<Speaker1>: do you get it because I don't get it

Reference

the real the more old school and all like

Base Model Prediction

The real The more old school You know like

Fine-Tuned Model Prediction

the real the more old school you know like

MERaLiON Model Prediction

<Speaker1>: The real, the more old school and all like.

Reference

not to say it's not very cheap to actually go there it's quite expensive

Base Model Prediction

Not to say it's not very cheap to actually go there, it's quite expensive.

Fine-Tuned Model Prediction

not to say it's not very cheap to actually go there it's quite expensive

MERaLiON Model Prediction

<Speaker1>: not to say it's not very cheap to actually go there, It's quite expensive.

Reference

when we climb all that

Base Model Prediction

Maybe climb on that.

Fine-Tuned Model Prediction

when you climb all that

MERaLiON Model Prediction

<Speaker1>: when you climb all that

Reference

no no not wearing slipper

Base Model Prediction

No, no, no, I mean,

Fine-Tuned Model Prediction

no no not wearing slippers

MERaLiON Model Prediction

<Speaker1>: no no not wearing slippers

Reference

with the aircon on and all

Base Model Prediction

Alright, so it's very very

Fine-Tuned Model Prediction

with the aircon on and all

MERaLiON Model Prediction

<Speaker1>: The economy is very, very.

Reference

or the routine maintenance or the writing of sop

Base Model Prediction

all the routine maintenance, all the writing of SOP.

Fine-Tuned Model Prediction

all the routine maintenance all the writing of SOP

MERaLiON Model Prediction

<Speaker1>: all the routine maintenance or the writing of Sops

Reference

once you're too cute

Base Model Prediction

And so, he describes

Fine-Tuned Model Prediction

once you're too cute

MERaLiON Model Prediction

<Speaker1>: And describe?

Reference

is it

Base Model Prediction

Okay, me?

Fine-Tuned Model Prediction

maybe

MERaLiON Model Prediction

<Speaker1>: Okay, we.

Reference

you you talk you you said that you have seven siblings

Base Model Prediction

You said that you have seven siblings.

Fine-Tuned Model Prediction

you you talk you you said that you have seven siblings

MERaLiON Model Prediction

<Speaker1>: you you talk you said that you have seven siblings

Reference

so you want to be a do~ doraemon

Base Model Prediction

So you want to be a Doraemon?

Fine-Tuned Model Prediction

so you want to be a do doremon

MERaLiON Model Prediction

<Speaker1>: so you want to be a ** dorimon?

Reference

<Speaker1>: ya it's no no seats [ah] we went all the way to the front I was like I was like I was like I was like this close like about three metres away from Jay-#Chou# I was like if I stretched out I could have touched him you know ya like like that's that's how close and then that was like one of the best thing that happened like I really like Jay-#Chou# I think is very interesting <Speaker2>: I get touch him already <Speaker1>: (uh) he's a very good singer next to JJ-#Lin# [lah] most people like JJ-#Lin# more in Singapore but I think Jay-#Chou# is (um) like his song better <Speaker2>: ya I think Jay-#Chou# also deserves a chance also to in Singapore also I think his fandom is also growing ya I think that's one bes~ the best thing to go and happen in Singapore is that we have <Speaker1>: correct correct

Base Model Prediction

There was no seats. We went over to the front. I was like this close, about 3 meters away from Jay Chou. I was like, if I stretch out, I'm going to touch him. I can touch him already. That's how close I was. Then there's like, what the best thing that happened. I really like Jay Chou. I think he's very interesting. He's a very good singer. Next to JJ Lin. Most people like JJ Lin more than Singapore, but I think Jay Chou is something like that. Yeah, I think Jay Chou also deserves a chance in Singapore. I think his fandom is also growing. Yeah, I think that's one of the best things.

Fine-Tuned Model Prediction

ya there's no no seats lah we went all the way to the front I was like I was like I was like this close like about three meters away from Jay Chou I was like if I stretch out I could have touched him you know ya like like that's that's how close then that's like one of the best thing that happen I really like Jay Chou I think it's very interesting uh he's a very good singer next to JJ Lin lah most people like JJ Lin more in Singapore but I think Jay Chou is mm like he's some better

MERaLiON Model Prediction

<Speaker1>: Ya, it's no seats [lah] We don't even go to the front. I was like I was like. I was like I was like this close like about three meters away from Jay Chou. I was like if I stretch out my hand, you can touch him already. <Speaker2>: You know how to touch me already. <Speaker1>: Ya like like that's That's how close then there's like what? The best thing happened? I really like Jay Chou. Think is very interesting. (uh) He's a very good singer next to Jj Lin. Like most people like Jj Lin more in Singapore, but I think Jay Chou is (mm) like that one better correct. <Speaker2>: Ya, I think Jay Chou also deserve a chance also in Singapore. Also, I think his fandom also growing ya. I think that's one of the best band in Singapore. <Speaker1>: Correct, correct.

Reference

<Speaker1>: ya okay around that should consider as okay can <Speaker2>: the same okay then I have a cage green cage with a yellow base and a rabbit white rabbit okay <Speaker1>: does it say buy me <Speaker2>: no <Speaker1>: okay mine says buy me <Speaker2>: okay your bunny sign where is it <Speaker1>: it's at the top it's the on the front on the top side <Speaker2>: on the top of the okay on the top of the cage

Base Model Prediction

Yeah okay, that should consider us. Okay, can. Okay, and then I have a cage, green cage with a yellow base and a rabbit, white rabbit. Does it say by me? No. Okay, mine says by me. Okay, your by me sign, where is it? It's at the top, it's on the front, on the top side. On the top of the, okay, on the top of the cage.

Fine-Tuned Model Prediction

ya okay around that should consider as okay can okay and then I have a cage green cage with a yellow base and a rabbit white rabbit mmhmm does it say buy me no okay mine says buy me okay your buy me sign where is it it's at the top it's on the front on the top side on the top of the okay on the top of the cage

MERaLiON Model Prediction

<Speaker1>: Ya, okay then around that should consider as okay can? <Speaker2>: Okay, and then I have a cage green cage with (uh) yellow base and a rabbit white rabbit. <Speaker1>: (mmhmm) <Speaker2>: Okay. <Speaker1>: Does it say by me? <Speaker2>: No. <Speaker1>: Okay, mine says By Me. <Speaker2>: Okay, your buy me sign where is it? <Speaker1>: It's at the top. It's on the under front on the top side. <Speaker2>: On the top of the okay on the top of the cage.

Reference

<Speaker1>: the sun or is he facing towards the book <Speaker2>: yeap yeap <Speaker1>: okay okay how many buttons does your bear have <Speaker2>: three white <Speaker1>: three white buttons right

Base Model Prediction

The sun? Or is he facing towards the books? Sun. Okay, how many buttons does your bear have? Three white. Three white buttons, right?

Fine-Tuned Model Prediction

the sun or is he facing towards the books okay okay how many buttons does your bear have three white buttons right

MERaLiON Model Prediction

<Speaker1>: The sun, or is he facing towards the books? <Speaker2>: This one. <Speaker1>: Okay, okay, how many buttons does your bear have? <Speaker2>: Three white. <Speaker1>: Three white buttons, right?

Reference

<Speaker1>: okay so I don't think there's any difference in this one <Speaker2>: okay I think it's the top right hand corner then <Speaker1>: okay I suppose all about even more words okay I suppose that will be where <Speaker2>: ya I tell you it will be there [lah] <Speaker1>: maybe we describe this in too much detail <Speaker2>: I think so too <Speaker1>: my condolences whoever transcribes this okay so let's see on the top right there's a large build rectangular box box building box shaped building (uh) there's a sign in the a sign in the top middle saying bar it's a brown background

Base Model Prediction

Okay, so I don't think there's any differences in this one. Okay, I think it's the top right hand corner. Okay, I suppose- oh, we've got even more words. Okay, I suppose- Yeah, I thought you'd be there. Maybe we described this in too much detail. I think so too. Oh, my condolences whoever transcribes this. Okay, so let's see. On the top right, there's a large build- uh, rectangular box- box building? Box-shaped building. Uh, there's a sign in the- a sign in the top middle saying PAR. It's a brown background.

Fine-Tuned Model Prediction

okay so I don't think there's any differences in this one okay I suppose oh got even more words okay I suppose that I will probably maybe we describe this in too much detail oh my condolences whoever transcribes this okay so let's see on the top right there's a large build uh rectangular box box building box shaped building uh there's a sign in the sign in the top middle saying bar it's a brown background

MERaLiON Model Prediction

<Speaker1>: Okay, so I don't think there's any differences in this one. <Speaker2>: K, I think it's a top right hand corner. <Speaker1>: Okay, I suppose [oh] got even more words. Okay? I suppose that's probably where you are at. <Speaker2>: Ya, I am really there. [ah] <Speaker1>: Then we describe this in too much detail. (uh) my condolences to whoever transcribes this. Okay, So let's see on the top right there's a large build rectangular box building, box shape building. (uh) There's a sign in the sign in the top middle saying bar. It's a brown background.

Reference

<Speaker1>: [ah] even the NTUC (uh) that NTUC the the thing is that the government also like like (uh) like not very encouraging people to do entrepreneur though they are though they are encourage [ah] in that sense [lah] but I think it's #wayang# [ah] the like like <Speaker2>: you know this this is all (uh)

Base Model Prediction

Even the NTUEC, the thing is that the government also not very encouraging people to do entrepreneur. Though they are encouraged in that sense, but I think it's wayang. You know, this is all...

Fine-Tuned Model Prediction

uh even the NTUC ah the NTUC the the thing is that the government also like like uh like not very encouraging people to do entrepreneur though they are though they are encourage ah in that sense ah but I think it's wayang ah ya like like

MERaLiON Model Prediction

<Speaker1>: [ah] even that Ntuc, [ah] the Ntuc, The The thing is that the government also like like (uh) like not very encouraging people to do entrepreneur though they are, though they are encourage ya in that sense, [lah] but I think it's more yang [lah] <Speaker2>: You know this, this is all (uh)

Reference

<Speaker1>: also I think because there is a bar nearby right in Singapore #Sentosa# there are also many bars in the at the beach so if there are bars right there are bound to be some (um) glasses shards on the sand so I guess it's to prevent you know getting cuts on the leg and the feet right that's why we wear shoes to prevent cuts <Speaker2>: [oh] I see

Base Model Prediction

Also, I think because there is a bar nearby right in Singapore Sentosa there are also many bars in the at a beach so if there are bars right there are bound to be some Glasses shards on the sand so I guess is to prevent, you know getting cuts on the leg On the feet right? That's why we wear shoes to prevent cuts Oh I see

Fine-Tuned Model Prediction

ya oh I see

MERaLiON Model Prediction

<Speaker1>: Also, I think because there is a bar nearby right in Singapore Sentosa, there are also many bars in the at the beach. So if there are bars right, they're bound to be some (um) glasses shards on the sand, so I guess it's to prevent you know getting cuts on the leg ya on the feet, Right that's why we wear shoes to prevent cuts. <Speaker2>: [oh] I see.

Reference

<Speaker1>: okay I'm gonna always have a ring here correct but that particular ring whatever you give right okay one thing I've okay I I am clumsy ya okay I is not I try to be s~ very safe I bang my ownself everywhere I go <Speaker2>: bang your feet everywhere you go <Speaker1>: of course I'll take care of it but if it's so

Base Model Prediction

Okay, I'm gonna always have a ring here correct, but a particular ring whatever you give right Okay one thing I've okay, I I am clumsy ah Okay, I it's not I try to be very safe. I bang my own self wherever I go Of course, I'll take care of it, but if it's so

Fine-Tuned Model Prediction

okay I'm gonna always have a ring here correct but that particular ring whatever you give right okay one thing I've okay I I am clumsy ah okay I is not I try to be very safe I bang my own self wherever I go of course I'll take care of it but if it's so

MERaLiON Model Prediction

<Speaker1>: Okay, I'm gonna always have a ring here correct, but that particular ring whatever you give right? Okay, one thing I've okay, I am clumsy. [ah] <Speaker2>: Ya. <Speaker1>: Okay, I is not. <Speaker2>: It's okay to be safe. <Speaker1>: I try to be very safe. I bring my own self wherever I go. Of course, I will take care of it, but if it's so.

Reference

<Speaker1>: okay basically it's a long story (uh) it's way before I got to know you (uh) <Speaker2>: okay <Speaker1>: K basically we we were young I was young back then so when my past was a bit colourful ya I think you should know so I had a I used to have a best (uh) best friend <Speaker2>: okay <Speaker1>: basically wherever we go

Base Model Prediction

Okay, basically... It's a long story. It's way before I got to know you. Okay. Basically, I was young back then so my past was a bit colourful. I think you should know. So, I used to have a best friend. Basically, wherever we go,

Fine-Tuned Model Prediction

okay basically it's a long story uh it's way before I got to know you uh K basically we we were young I was young back then so I'm my past was a bit colourful ya I think you should know so I had I used to have a best uh best friend basically wherever we go

MERaLiON Model Prediction

<Speaker1>: Okay, basically it's a long story. (uh) It's way before I got to know you. <Speaker2>: Okay. <Speaker1>: [ah] K. Basically we were young. I was young back then, so my past was a bit colourful ya. I think you should know, so I had. I used to have a best (uh) best friend. <Speaker2>: Okay. <Speaker1>: Basically wherever we go.

Reference

<Speaker1>: three [ah] I have a lot here you know three six I think mine g~ !huh! <Speaker2>: no I know I know she sh~ I know he is (uh) you know holding (uh) something like you know a a basket like that <Speaker1>: a bas~ like a a like a like a thre~ a basket [ha] how many peaches are there a lot [lah] <Speaker2>: a lot a lot but then his right hand [ah] he still (uh) string up know (uh) three peaches you know <Speaker1>: his right hand got three peaches [ah] <Speaker2>: ya ya ya he use ya ya string <Speaker1>: [oh] holding three peaches [ah] [oh] mine don't !huh! string [ah] [orh] d~ you mean the peaches tie to a string <Speaker2>: ya ya ya ya ya

Base Model Prediction

Three, I have a lot here, you know. Three, six. No, I know, I know she, I know he is, you know, holding something like, you know, a basket. A basket, huh? Hmm, a lot. How many pictures are there? A lot, lah. A lot. But then, his right hand, he still string up, you know, three pictures, you know. His right hand has three pictures, ah? Yeah, yeah, yeah. Holding three pictures, ah? Yeah, yeah, string. Oh, mine don't. Huh, string, huh? Ah. Oh, you mean the pictures tied to a string? Yeah, yeah, yeah, yeah. Oh, mine don't.

Fine-Tuned Model Prediction

three ah I have a lot here you know three six I don't know what ah no I know I know she shi I know he is uh you know holding uh something like you know a a basket like that mm a lot a lot but then his right hand ah he still uh string up you know uh three peaches you know ya ya ya he use ya ya string ah ah oh that mean the peaches tie to the string ya ya ya ya

MERaLiON Model Prediction

<Speaker1>: Three, [ah] I have a lot here. You know three, six, seven, eight, nine, ten. <Speaker2>: No, I know. I know she. She. I know he's (uh) you know holding something like you know, a basket like that. <Speaker1>: The (uh) (uh) (uh) (uh) like (uh) basket [ah] how many peaches there? A lot [lah] <Speaker2>: (mm) a lot, but then his right hand. [ah] he still (uh) string out. Know (uh) three peaches, you know. <Speaker1>: His right hand got three peaches. [ah] ya, ya, ya or hold three peaches. [ah] <Speaker2>: He holds you three peaches. [ah] ya, ya, ya string. <Speaker1>: Mine don't !huh! string [ha] [oh] they mean the peaches tied to the string. <Speaker2>: Ya, ya, ya, ya.

Reference

<Speaker1>: doing or learning all sorts of (uh) hard skills such as (uh) tent pitching tying knots marching ya so <Speaker2>: some of the skills (mm) <Speaker1>: but this is but this is not my favourite CCA as well ya <Speaker2>: [oh] why is it so <Speaker1>: actually my favourite CCA is to be in a drama club because I'll get to

Base Model Prediction

doing learning all sorts of uh hard skills such as tan pitching tying knots matching yeah so some of this is but this is not my favorite cca as well why is it so actually my favorite cca is to be in the drama club because i get to

Fine-Tuned Model Prediction

doing learning all sorts of uh hard skills such as uh tent pitching tying knots uh marching ya so but this is but this is not my favourite CCA as well ya actually my favourite CCA is to be in a drama club because I get to

MERaLiON Model Prediction

<Speaker1>: Doing learning all sorts of (uh) hard skills, such as (uh) tent pitching tying knots marching ya so? <Speaker2>: Some of the skills. <Speaker1>: But this is, but this is not my favourite Cca as well. <Speaker2>: [oh] why is it so? <Speaker1>: Actually, my favourite Cca is to be in a drama club because I get to.